We propose a novel domain adaptive action detection approach and a new
a...
Current methods for spatiotemporal action tube detection often extend a
...
For an autonomous robotic system, monitoring surgeon actions and assisti...
Humans approach driving in a holistic fashion which entails, in particul...
In this thesis, we focus on video action understanding problems from an
...
In this work, we take aim towards increasing the effectiveness of surgic...
In this paper, we propose Two-Stream AMTnet, which leverages recent adva...
Building correspondences across different modalities, such as video and
...
Recently, three dimensional (3D) convolutional neural networks (CNNs) ha...
In this work, we present a method to predict an entire `action tube' (a ...
Current state-of-the-art methods solve spatiotemporal action localisatio...
We present the new Road Event and Activity Detection (READ) dataset, des...
Current state-of-the-art human action recognition is focused on the
clas...
Current state-of-the-art action detection systems are tailored for offli...
We present a deep-learning framework for real-time multiple spatio-tempo...
In this work, we propose an approach to the spatiotemporal localisation
...
Current state-of-the-art human activity recognition is focused on the
cl...